CD2 Is a Novel Immune-Related Prognostic Biomarker of Invasive Breast Carcinoma That Modulates the Tumor Microenvironment

Apolipoprotein A-1 downregulation promotes basal-like breast cancer cell proliferation and migration associated with DNA methylation

Apolipoprotein A-I (APOA1) performs different roles in different subtypes of breast cancer. It is hypothesized to function as a tumor suppressor in basal-like breast cancer (BLBC). However, the specific role of APOA1 in BLBC and its underlying mechanisms remain unknown. The findings of the present study demonstrated a positive correlation between the expression level of APOA1 and the overall survival of patients with BLBC. Ectopic expression of APOA1 effectively inhibits the proliferation and metastasis of BLBC cells in vitro, and these effects are closely related to DNA methylation. To the best of our knowledge, the present study is the first to report increased methylation of the promoter region and decreased methylation of the structural genes of APOA1 in BLBC cells. These alterations resulted in the downregulation of APOA1 expression and suppression of BLBC tumor growth. Collectively, the results of the present study suggested that APOA1 mRNA expression is negatively regulated by DNA methylation in BLBC. Therefore, low expression of APOA1 may be a potential risk biomarker to predict survival in patients with BLBC.

Immunotherapy, prognostic, and tumor biomarker based on pancancer analysis, SMARCD3

BACKGROUND

SMARCD3 has recently been shown to be an important gene affecting cancer, playing an important role in medulloblastoma and pancreatic ductal adenocarcinoma. Therefore, we conducted this research to investigate the potential involvement of SMARCD3 across cancers and to offer recommendations for future studies.

METHODS

Utilizing information on 33 malignancies in the UCSC Xena database, SMARCD3 expression and its prognostic value were assessed. The tumor microenvironment was evaluated with the "CIBERSORT" and "ESTIMATE" algorithms. SMARCD3 and immune-related genes were analyzed using the TISIDB website. The pathways related to the target genes were examined using GSEA. MSI (microsatellite instability), TMB (tumor mutational burden), and immunotherapy analysis were used to evaluate the impact of target genes on the response to immunotherapy.

RESULTS

There is heterogeneity in terms of the expression and prognostic value of SMARCD3 among various cancers, but it is a risk factor for many cancers including uterine corpus endometrial cancer (UCEC), renal clear cell carcinoma (KIRC), and gastric adenocarcinoma (STAD). GSEA revealed that SMARCD3 is related to chromatin remodeling and transcriptional activation, lipid metabolism, and the activities of various immune cells. The TMB and MSI analyses suggested that SMARCD3 affects the immune response efficiency of KIRC, LUAD and STAD. Immunotherapy analysis suggested that SMARCD3 may be a potential immunotherapy target. RT-qPCR demonstrated the variation in SMARCD3 expression in KIRC, LUAD, and STAD.

CONCLUSION

Our study revealed that SMARCD3 affects the prognosis and immunotherapy response of some tumors, providing a direction for further research on this gene.

The endonuclease FEN1 mediates activation of STAT3 and facilitates proliferation and metastasis in breast cancer

BACKGROUND

The metastasis accounts for most deaths from breast cancer (BRCA). Understanding the molecular mechanisms of BRCA metastasis is urgently demanded. Flap Endonuclease 1 (FEN1), a pivotal factor in DNA metabolic pathways, contributes to tumor growth and drug resistance, however, little is known about the role of FEN1 in BRCA metastasis.

METHODS AND RESULTS

In this study, FEN1 expression and its clinical correlation in BRCA were investigated using bioinformatics, showing being upregulated in BRCA samples and significant relationships with tumor stage, node metastasis, and prognosis. Immunohistochemistry (IHC) staining of local BRCA cohort indicated that the ratio of high FEN1 expression in metastatic BRCA tissues rose over that in non-metastatic tissues. The assays of loss-of-function and gain-of-function showed that FEN1 enhanced BRCA cell proliferation, migration, invasion, xenograft growth as well as lung metastasis. It was further found that FEN1 promoted the aggressive behaviors of BRCA cells via Signal Transducer and Activator of Transcription 3 (STAT3) activation. Specifically, the STAT3 inhibitor Stattic thwarted the FEN1-induced enhancement of migration and invasion, while the activator IL-6 rescued the decreased migration and invasion caused by FEN1 knockdown. Additionally, overexpression of FEN1 rescued the inhibitory effect of nuclear factor-κB (NF-κB) inhibitor BAY117082 on phosphorylated STAT3. Simultaneously, the knockdown of FEN1 attenuated the phosphorylation of STAT3 promoted by the NF-κB activator tumor necrosis factor α (TNF-α).

CONCLUSIONS

These results indicate a novel mechanism that NF-κB-driven FEN1 contributes to promoting BRCA growth and metastasis by STAT3 activation.

Development and implementation of a prognostic model for clear cell renal cell carcinoma based on heterogeneous TLR4 expression

Objective

Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cell carcinomas and has the worst prognosis, originating from renal tubular epithelial cells. Toll-like receptor 4 (TLR4) plays a crucial role in ccRCC proliferation, infiltration, and metastasis. The aim of this study was to construct a prognostic scoring model for ccRCC based on TLR4 expression heterogeneity and to explore its association with immune infiltration, thereby providing insights for the treatment and prognostic evaluation of ccRCC.

Methods

Using R software, a differential analysis was conducted on normal samples and ccRCC samples, and in conjunction with the KEGG database, a correlation analysis for the clear cell renal cell carcinoma pathway (hsa05211) was carried out. We observed the expression heterogeneity of TLR4 in the TCGA-KIRC cohort and identified its related differential genes (TRGs). Based on the expression levels of TRGs, consensus clustering was employed to identify TLR4-related subtypes, and further clustering heatmaps, principal component, and single-sample gene set enrichment analyses were conducted. Overlapping differential genes (ODEGs) between subtypes were analysed, and combined with survival data, univariate Cox regression, LASSO, and multivariate Cox regression were used to establish a prognostic risk model for ccRCC. This model was subsequently evaluated through ROC analysis, risk factor correlation analysis, independent prognostic factor analysis, and intergroup differential analysis. The ssGSEA model was employed to explore immune heterogeneity in ccRCC, and the performance of the model in predicting patient prognosis was evaluated using box plots and the oncoPredict software package.

Results

In the TCGA-KIRC cohort, TLR4 expression was notably elevated in ccRCC samples compared to normal samples, correlating with improved survival in the high-expression group. The study identified distinct TLR4-related differential genes and categorized ccRCC into three subtypes with varied survival outcomes. A risk prognosis model based on overlapping differential genes was established, showing significant associations with immune cell infiltration and key immune checkpoints (PD-1, PD-L1, CTLA4). Additionally, drug sensitivity differences were observed between risk groups.

Conclusion

In the TCGA-KIRC cohort, the expression of TLR4 in ccRCC samples exhibited significant heterogeneity. Through clustering analysis, we identified that the primary immune cells across subtypes are myeloid-derived suppressor cells, central memory CD4 T cells, and regulatory T cells. Furthermore, we successfully constructed a prognostic risk model for ccRCC composed of 17 genes. This model provides valuable references for the prognosis prediction and treatment of ccRCC patients.

ATP2C2 as a novel immune-related marker that defines the tumor microenvironment in triple-negative breast cancer

Background

Triple-negative breast cancer (TNBC) is an aggressive cancer that affects about 13/100,000 women yearly. Patients with TNBC are often resistant to endocrine and molecular targeted therapy, making clinical treatment challenging. Researches indicate that tumor microenvironment (TME) is related to prognosis in many cancers. Therefore, we aim to identify TME immune-related biomarkers to enhance the prognosis and immunotherapy efficacy in patients with TNBC.

Methods

The bulk mRNA transcriptome data and clinical information of the (GSE58812) and (GSE25055) datasets were downloaded from the Gene Expression Omnibus (GEO) database, and the ESTIMATE algorithm was used to calculate the ImmuneScore, StromalScore, and ESTIMATEScore. Patients were divided into low and high groups according to the quartiles of ImmuneScore, StromalScore, and the median of ESTIMATEScore to filter differential expression genes (DEGs), respectively. The DEGs were then evaluated using univariate and multivariate Cox regression to identify TME-related genes and its association with survival rate for the construction of a TMErisk model with three biomarkers. Then Gene Expression Profiling Interactive Analysis (GEPIA) and The Cancer Genome Atlas (TCGA) data were used to compare the gene expression in cancer and normal tissues. xCell analysis calculated the proportion of tumor-infiltrating immune cells in low and high expression of ATPase Secretory Pathway Ca2+ Transporting 2 (ATP2C2). In addition, samples from 20 TNBC patients admitted to our institution were used for immunohistochemical (IHC) examination.

Results

Three immune-related DEGs were identified, including prolyl 3-hydroxylase 2 (P3H2), sodium voltage-gated channel beta subunit 3 (SCN3B), and ATP2C2 and a TMErisk model was constructed and validated. However, only ATP2C2 was selected for further analysis. ATP2C2 mRNA level of TNBC patients was higher than that of normal breast tissue. Survival analysis showed that patients with high expression of ATP2C2 had a bad prognosis. xCell analysis demonstrated that the expression of ATP2C2 was associated with 16 kinds of tumor-infiltrating immune cells. Protein expression of ATP2C2 in TNBC tissues was higher compared to paired normal tissues in IHC.

Conclusions

This study constructed and validated a TMErisk model that can effectively predict 3- and 5-year survival rate for TNBC patients. TNBC patients with lower expression of ATP2C2 had a good prognosis.

Integrated transcriptome analysis identifies APPL1/RPS6KB2/GALK1 as immune-related metastasis factors in breast cancer

The aim of this study is to investigate the prognostic immune-related factors in breast cancer (BC) metastasis. The gene expression chip GSE159956 was downloaded from the gene expression omnibus database. Differentially expressed genes (DEGs) were selected using GEO2R online tools based on lymph node and metastasis status. The intersected survival-associated DEGs were screened from the Kaplan-Meier curve. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) annotation analyses were performed to determine the survival-associated DEGs. Immune-related prognostic factors were screened based on immune infiltration. The screened prognostic factors were verified by the Cancer Genome Atlas (TCGA) database and single-sample gene set enrichment analysis (ssGSEA). As a result, twenty-eight upregulated and three downregulated genes were generated by the survival analysis. The enriched GO and KEGG pathways were mostly correlated with "regulation of cellular amino acid metabolic process," "proteasome complex," "endopeptidase activity," and "proteasome." Six of 19 (17 upregulated and 2 downregulated) immune-related prognostic factors were verified by the TCGA database. Four immune-related factors were obtained after ssGSEA, and three significant immune-related factors were selected after univariate and multivariate analyses. Based on the risk score receiver operating characteristic, the three immune-related prognosis factors could be potential biomarkers of BC metastasis. In conclusion, APPL1, RPS6KB2, and GALK1 may play a pivotal role as potential biomarkers for prediction of BC metastasis.

Identification of INSRR as an immune-related gene in the tumor microenvironment of glioblastoma by integrated bioinformatics analysis

Gliomas are the most common malignant tumors in the central nervous system. The tumor microenvironment (TME) plays a crucial role in tumor proliferation, invasion, angiogenesis, and immune escape. However, little is known about TME in gliomas. The purpose of this study was to explore the biomarkers associated with TME in glioblastoma (GBM) to predict immunotherapy effectiveness and prognosis in patients. Based on RNA-seq transcriptome data and clinical features of 1222 samples (113 normal samples and 1109 tumor samples) in The Cancer Genome Atlas (TCGA) database, the ImmuneScore, StromalScore, and ESTIMATEScore were calculated by ESTIMATE algorithm. The differentially expressed genes (DEGs) and differentially mutated genes (DMGs) were determined in the TCGA GBM cohort. Furthermore, gene set enrichment analysis (GSEA) was used to investigate the enrichment pathways of INSRR genes with abnormal expression. The proportion of tumor-infiltrating immune cells (TIICs) was evaluated by CIBERSORT. Frequent mutations of TP53, EGFR, and PTEN occurred in high and low immune scores. The cross-analysis of DEGs and DMGs revealed that INSRR was an immune-related biomarker in the TCGA GBM cohort. According to GSEA, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway with INSRR abnormal expression were IgA-produced intestinal immune network and Alzheimer's disease, oxidative phosphorylation, and Parkinson's disease, respectively. Additionally, INSRR expression was correlated with dendritic cells activated, dendritic cells resting, T cells CD8, and T cell gamma delta. INSRR is associated with the immune microenvironment in GBM and is used as a biomarker to predict immune invasion.

Systematic pan-cancer analysis of the potential tumor diagnosis and prognosis biomarker P4HA3

Purpose: Prolyl 4-hydroxylase subunit alpha 3 (P4HA3) is implicated in several cancers' development. However, P4HA3 has not been reported in other cancers, and the exact mechanism of action is currently unknown. Materials and methods: First, the expression profile of P4HA3 was analyzed using a combination of the University of California Santa Cruz (UCSC) database, Cancer Cell Line Encyclopedia (CCLE) database, and Genotype-Tissue Expression (GTEx) database. UniCox and Kaplan-Meier were used to analyze the predictive value of P4HA3. The expression of P4HA3 was analyzed in clinical staging, immune subtypes, and Molecular subtypes. Secondly, the correlation of P4HA3 with immunomodulatory genes, immune checkpoint genes, RNA modification genes, immune cell infiltration, cancer-related functional status, tumor stemness index, DNA mismatch repair (MMR) genes and DNA Methyltransferase was examined. The role of P4HA3 in DNA methylation, copy number variation (CNV), mutational status, tumor mutational burden (TMB), and microsatellite instability (MSI) was also analyzed. In addition, gene set enrichment analysis (GSEA) was used to explore the potential functional mechanisms of P4HA3 in pan-cancer. Finally, P4HA3-related drugs were searched in CellMiner, Genomics of Drug Sensitivity in Cancer (GDSC), and Cancer Therapeutics Response Portal (CTRP) databases. Results: P4HA3 is significantly overexpressed in most cancers and is associated with poor prognosis. P4HA3 is strongly associated with clinical cancer stage, immune subtypes, molecular subtypes, immune regulatory genes, immune checkpoint genes, RNA modifier genes, immune cell infiltration, cancer-related functional status, tumor stemness index, MMR Gene, DNA Methyltransferase, DNA methylation, CNV, mutational status, TMB, and MSI are closely related. Available enrichment analysis revealed that P4HA3 is associated with the epithelial-mesenchymal transition and immune-related pathways. There are currently 20 drugs associated with P4HA3. Conclusion: In human pan-cancer, P4HA3 is associated with poor patient prognosis and multiple immune cells and may be a novel immunotherapeutic target. It may act on tumor progression through the epithelial-mesenchymal transition (EMT) pathway.

Identification of prognosis-related gene features in low-grade glioma based on ssGSEA

Low-grade gliomas (LGG) are commonly seen in clinical practice, and the prognosis is often poor. Therefore, the determination of immune-related risk scores and immune-related targets for predicting prognoses in patients with LGG is crucial. A single-sample gene set enrichment analysis (ssGSEA) was performed on 22 immune gene sets to calculate immune-based prognostic scores. The prognostic value of the 22 immune cells for predicting overall survival (OS) was assessed using the least absolute shrinkage and selection operator (LASSO) and univariate and multivariate Cox analyses. Subsequently, we constructed a validated effector T-cell risk score (TCRS) to identify the immune subtypes and inflammatory immune features of LGG patients. We divided an LGG patient into a high-risk-score group and a low-risk-score group based on the optimal cutoff value. Kaplan-Meier survival curve showed that patients in the low-risk-score group had higher OS. We then identified the differentially expressed genes (DEGs) between the high-risk-score group and low-risk-score group and obtained 799 upregulated genes and 348 downregulated genes. The analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) show that DEGs were mainly concentrated in immune-related processes. In order to further explore the immune-related genes related to prognosis, we constructed a protein-protein interaction (PPI) network using Cytoscape and then identified the 50 most crucial genes. Subsequently, nine DEGs were found to be significantly associated with OS based on univariate and multivariate Cox analyses. It was further confirmed that CD2, SPN, IL18, PTPRC, GZMA, and TLR7 were independent prognostic factors for LGG through batch survival analysis and a nomogram prediction model. In addition, we used an RT-qPCR assay to validate the bioinformatics results. The results showed that CD2, SPN, IL18, PTPRC, GZMA, and TLR7 were highly expressed in LGG. Our study can provide a reference value for the prediction of prognosis in LGG patients and may help in the clinical development of effective therapeutic agents.

C1QA, C1QB, and GZMB are novel prognostic biomarkers of skin cutaneous melanoma relating tumor microenvironment

Skin cutaneous melanoma (SKCM) is the most lethal form of skin cancers owing to high invasiveness and high metastatic potential. Tumor microenvironment (TME) provides powerful evidences for discerning SKCM, raising the prospect to identify biomarkers of SKCM. Based on the transcriptome profiles of patients with SKCM and the corresponding clinical information from The Cancer Genome Atlas (TCGA), we used ESTIMATE algorithm to calculate ImmuneScore and StromalScore and identified the TME-Related differentially expressed genes (DEGs), than the intersected TME-Related DEGs were used for subsequent functional enrichment analysis. Protein-protein interaction (PPI) analysis was used to identify the functionality-related DEGs and univariate Cox regression analysis was used to identify the survival-related DEGs. Furthermore, SKCM-related DEGs were identified based on two Gene Expression Omnibus (GEO) datasets. Finally, we intersected functionality-related DEGs, survival-related DEGs, and SKCM-related DEGs, ascertaining that six DEGs (CCL4, CXCL10, CCL5, GZMB, C1QA, and C1QB) function as core TME-related genes (CTRGs). Significant differences of GZMB, C1QA, and C1QB expressions were found in gender and clinicopathologic staging of SKCM. High levels of GZMB, C1QA, and C1QB expressions were associated with favorable prognosis. Gene set enrichment analysis (GSEA) showed that cell-cell interaction, cell behavior, and intracellular signaling transduction may be mainly involved in both C1QA, C1QB and GZMB expressions and metabolism of phospholipid and amino acid, transcription, and translation may be implicated in low GZMB expressions. C1QA, C1QB, and GZMB are novel SKCM-relating CTRGs, providing promising immune-related prognostic biomarkers for SKCM.

[CD40LG is a novel immune- and stroma-related prognostic biomarker in the tumor microenvironment of invasive breast cancer]

OBJECTIVE

To identify tumor microenvironment (TME)- related genes associated with the occurrence of invasive breast cancer as potential prognostic biomarkers and therapeutic targets.

METHODS

RNA transcriptome data and clinically relevant data were retrieved from TCGA database, and the StromalScore and ImmuneScore were calculated using the ESTIMATE algorithm. The differentially expressed genes (DEGs) were screened by taking the intersection. A protein- protein interaction network was established, and univariate COX regression analysis was used to identify the core genes among the DEGs. A core gene was selected for GSEA and CIBERSORT analysis to determine the function of the core gene and the proportion of tumor-infiltrating immune cells, respectively. Western blotting and qRT-PCR were performed to verify the expression level of CD40LG in breast cancer cell lines and clinical specimens.

RESULTS

A total of 1222 samples (124 normal and 1098 tumor samples) were extracted from TCGA for analysis, from which 487 DEGs were identified. These genes were mainly enriched in immune-related pathways, and crossover analysis identified 11 key genes (CD40LG, ITK, CD5, CD3E, SPN, IL7R, CD48, CCL19, CD2, CD52, and CD2711) associated with breast cancer TME status. CD40LG was selected as the core gene, whose high expression was found to be associated with a longer overall survival of breast cancer patients (P=0.002), and its expression level differed significantly with TNM stage and tumor size (P < 0.05). GSEA and CIBERSORT analyses indicated that CD40LG expression level was associated with immune activity in the TME. Western blotting and qRT-PCR showed that the protein and mRNA expression of CD40LG were significantly lower in breast cancer cells and cancer tissues than in normal breast cells and adjacent tissues.

CONCLUSIONS

The high expression of CD40LG in TME is positively correlated with the survival of patients with invasive breast cancer, suggesting its value as a potential new biomarker for predicting prognosis of the patients.

CCR5 as a Prognostic Factor in Lower-Grade Glioma is Involved in the Remodeling of the Tumor Microenvironment

Background: Lower-grade gliomas (LGGs) carry a high risk of malignant transformation, leading to severe neurologic deterioration and ultimately, death. The tumor microenvironment (TME) plays an essential role in tumor maintenance, progression, and immunotherapy resistance. Therefore, the LGG TME deserves comprehensive exploration for a novel therapeutic target.

Methods: The ESTIMATE algorithm was used to estimate infiltrating stromal and immune cells of LGG patients obtained from the Cancer Genome Atlas (TCGA) database. Kaplan–Meier analysis was performed to classify survival differences. TME-related differentially expressed genes were identified between the low- and high-immune/stromal groups. Hub genes were screened by constructing protein–protein interaction networks and performing the Cox regression analysis. Differential analysis, survival analysis, gene set enrichment analysis, and clinical relevance analysis specific to hub genes were evaluated by using the TCGA and the Chinese Glioma Genome Atlas datasets, and the results were validated by qRT-PCR, Western blotting, and immunohistochemistry in tissues from LGG patients.

Results: The immune and stromal components in TME were negatively related to patient prognosis. Differentially expressed genes sharing immune score and stromal score were mainly involved in the immune response. C-C chemokine receptor type 5 (CCR5), as only a hub gene, was significantly higher in LGG patients than normal patients and negatively correlated with the prognosis of patients. High-expression CCR5 was positively related to immune-related and tumor progression pathways. CCR5 protein expression was higher in LGG with isocitrate dehydrogenase wildtype. Validated results showed that CCR5 was upregulated in LGG tissues at mRNA and protein levels and could affect immune cell infiltration. These results suggested that CCR5 was a potential indicator for the status of TME.

Conclusion: Glioma cells remodel the immune microenvironment through the high expression of CCR5 and lead to a poor prognosis in patients with LGG. The inhibition of CCR5 may contribute to the efficacy of LGG immunotherapy.

An Immune-Related Long Noncoding RNA Pair as a New Biomarker to Predict the Prognosis of Patients in Breast Cancer

Background: Immune-related long non-coding RNAs (irlncRNAs) might remodel the tumor immune microenvironment by changing the inherent properties of tumor cells and the expression of immune genes, which have been used to predict the efficacy of immunotherapy and the prognosis of various tumors. However, the value of irlncRNAs in breast cancer (BRCA) remains unclear.

Materials and Methods: Initially, transcriptome data and immune-related gene sets were downloaded from The Cancer Genome Atlas (TCGA) database. The irlncRNAs were extracted from the Immunology Database and Analysis Portal (ImmPort) database. Differently expressed irlncRNAs (DEirlncRNAs) were further identified by utilizing the limma R package. Then, univariate and multivariate Cox regression analyses were conducted to select the DEirlncRNAs associated with the prognosis of BRCA patients. In addition, the univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were performed to determine the DEirlncRNA pairs with the independent prediction capability of prognosis in BRCA patients. Finally, the chosen DEirlncRNA pair would be evaluated in terms of survival time, clinicopathological characteristics, tumor-infiltrating immune cells, immune checkpoints (ICs), signaling pathways, and potential small-molecule drugs.

Results: A total of 21 DEirlncRNA pairs were extracted, and among them, lncRNA MIR4435-2HG and lncRNA U62317.1 were chosen to establish a risk signature that served as an independent prognostic biomarker in BRCA patients. Patients in the high-risk group had a worse prognosis than those in the low-risk group, and they also had an abundance of infiltration of CD4+ T and CD8+ T cells to enhance the immune response to tumor cells. Furthermore, the risk signature showed a strong correlation with ICs, signaling pathways, and potential small-molecule drugs.

Conclusion: Our research revealed that the risk signature independent of specific DEirlncRNA pair expression was closely associated with the prognosis and tumor immune microenvironment in BRCA patients and had the potential to function as an independent prognostic biomarker and a predictor of immunotherapy for BRCA patients, which would provide new insights for BRCA accurate treatment.

Comprehensive Landscape of RRM2 with Immune Infiltration in Pan-Cancer

Simple Summary

RRM2 is a crucial subunit of ribonucleotide reductase. In this article, we provided a comprehensive analysis of RRM2 with immune infiltration in pan-cancer. We focused on the hotspots of ferroptosis-related gene RRM2 and immunotherapy. Via bioinformatics analysis, multiple indicators suggested that RRM2 high expression may enhance immunotherapy sensitivity. For the first time, we systematically analyzed the role of RRM2 in pan-cancer. We provided the prospect of RRM2 and immunotherapy for pan-cancer. Additionally, we proved the expression pattern, clinical value, prognostic value and potential pathways of RRM2 with different platforms. In particular, we confirmed RRM2 expression and function in bladder cancer in our clinical samples and cell lines. Collectively, we found that RRM2 is a novel prognostic biomarker, and these findings may aid in an improved understanding of the role of RRM2 and its clinical application in human cancers.

Abstract

As a crucial subunit of ribonucleotide reductase, RRM2 plays a significant part in DNA synthesis. This study aimed to elucidate the comprehensive landscape of RRM2 in human cancers. With different bioinformatics platforms, we investigated the expression pattern, prognostic significance, mutational landscapes, gene interaction network, signaling pathways and immune infiltration of RRM2 in tumors. We found that RRM2 expression was predominantly up-expressed in tumor tissues in most tumors. Concurrently, RRM2 expression was significantly associated with worse prognosis and tumor stage across TCGA cancers. Moreover, RRM2 high levels were critically associated with the infiltration of natural killer T cells and immune scores. RRM2 was positively related to immune checkpoints, tumor mutation burden, microsatellite instability, neoantigen, and cytotoxic T lymphocyte in several cancers, predicting effective response to immunotherapy. Meanwhile, a strong co-expression of RRM2 with immune-related genes was observed. Additionally, multiple Cox regression analysis showed that RRM2 was an independent prognostic factor in bladder cancer (BLCA). Eventually, we verified that RRM2 was overexpressed in BLCA clinical samples and cell lines. Blocking RRM2 could suppress BLCA cells’ growth and proliferation while enhancing sensitivity to cisplatin. This study provided a new perspective for understanding RRM2 in cancers and new strategies for tumor immunotherapy.

Identification and Validation of Immune Molecular Subtypes and Immune Landscape Based on Colon Cancer Cohort

Background

The incidence and mortality rates of colon adenocarcinoma (COAD), which is the fourth most diagnosed cancer worldwide, are high. A subset of patients with COAD has shown promising responses to immunotherapy. However, the percentage of patients with COAD benefiting from immunotherapy is unclear. Therefore, gaining a better understanding of the immune milieu of colon cancer could aid in the development of immunotherapy and suitable combination strategies.

Methods

In this study, gene expression profiles and clinical follow-up data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and molecular subtypes were identified using the ConsensusClusterPlus package in R. Univariate and multivariate Cox regression analyses were performed to evaluate the prognostic value of immune subtypes. The graph structure learning method was used to reduce the dimension to reveal the internal structure of the immune system. Weighted correlation network analysis (WGCNA) was performed to identify immune-related gene modules. Finally, western blotting was performed to verify the gene expression patterns in COAD samples.

Results

The results showed that 424 COAD samples could be divided into three subtypes based on 1921 immune cell-related genes, with significant differences in prognosis between subtypes. Furthermore, immune-related genes could be divided into five functional modules, each with a different distribution pattern of immune subtypes. Immune subtypes and gene modules were highly reproducible across many data sets. There were significant differences in the distribution of immune checkpoints, molecular markers, and immune characteristics among immune subtypes. Four core genes, namely, CD2, FGL2, LAT2, and SLAMF1, with prognostic significance were identified by WGCNA and univariate Cox analysis.

Conclusion

Overall, this study provides a conceptual framework for understanding the tumor immune microenvironment of colon cancer.

OAS3 is a Co-Immune Biomarker Associated With Tumour Microenvironment, Disease Staging, Prognosis, and Treatment Response in Multiple Cancer Types

2′,5′-oligoadenylate synthase (OAS) is a class of enzymes induced by interferons and mainly encoded by the OAS1, OAS2, and OAS3 genes, which activate the potential RNA enzymes to degrade viral mRNA, inhibit viral protein synthesis and promote apoptosis in virus-infected cells. OAS3 is associated with breast cancer prognosis. However, the expression and prognosis of OAS3 and tumour-infiltrating lymphocytes in pan-cancer remain unknown. In the present study, we have systematically investigated and confirmed the role of OAS3 in tumour immune infiltration, immune escape, tumour progression, response to treatment, and prognosis of different cancer types using various bioinformatics methods. The findings suggest that OAS3 is aberrantly expressed in almost all TCGA cancer types and subtypes and is associated with tumour staging, metastasis, and prognostic deterioration in different tumours. In addition, OAS3 expression is associated with the prognosis and chemotherapeutic outcomes of various cancers. In terms of immune-infiltrating levels, OAS3 expression is positively associated with the infiltration of immunosuppressive cells. These findings suggest that OAS3 is correlated with prognosis and immune-infiltrating levels.

PRRX1 Is a Novel Prognostic Biomarker and Facilitates Tumor Progression Through Epithelial–Mesenchymal Transition in Uveal Melanoma

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. UM develops and is sustained by inflammation and immunosuppression from the tumor microenvironment (TME). This study sought to identify a reliable TME-related biomarker that could provide survival prediction and new insight into therapy for UM patients. Based on clinical characteristics and the RNA-seq transcriptome data of 80 samples from The Cancer Genome Atlas (TCGA) database, PRRX1 as a TME- and prognosis-related gene was identified using the ESTIMATE algorithm and the LASSO–Cox regression model. A prognostic model based on PRRX1 was constructed and validated with a Gene Expression Omnibus (GEO) dataset of 63 samples. High PRRX1 expression was associated with poorer overall survival (OS) and metastasis-free survival (MFS) in UM patients. Comprehensive results of the prognostic analysis showed that PRRX1 was an independent and reliable predictor of UM. Then the results of immunological characteristics demonstrated that higher expression of PRRX1 was accompanied by higher expression of immune checkpoint genes, lower tumor mutation burden (TMB), and greater tumor cell infiltration into the TME. Gene set enrichment analysis (GSEA) showed that high PRRX1 expression correlated with angiogenesis, epithelial–mesenchymal transition (EMT), and inflammation. Furthermore, downregulation of PRRX1 weakened the process of EMT, reduced cell invasion and migration of human UM cell line MuM-2B in vitro. Taken together, these findings indicated that increased PRRX1 expression is independently a prognostic factor of poorer OS and MFS in patients with UM, and that PRRX1 promotes malignant progression of UM by facilitating EMT, suggesting that PRRX1 may be a potential target for UM therapy.

Racial differences in prostate tumor microenvironment: implications for disparate clinical outcomes and potential opportunities

Disparities in cancer incidence and outcome are common among the racial and ethnical minorities in the United States and are of significant social and clinical concern. Prostate cancer is the most commonly diagnosed non-cutaneous malignancy in American men and exhibits substantial racial disparities with African American men bearing the highest burden in terms of incidence and mortality. A multitude of factors, including socioeconomic, behavioral, and access to healthcare, have been implicated as the underlying causes of such disparities. More recent data also suggest that there are inherent molecular and biological differences in prostate tumors of patients having distinct racial backgrounds. Tumor microenvironment has tremendous impact on the course of cancer progression and clinical outcome and may also contribute to the racial disparities observed in prostate cancer. Therefore, a better understanding of critical differences in the tumor microenvironment components may provide newer directions to study the biological causes of prostate cancer health disparities and may identify novel therapeutic targets. This review discusses the findings related to the tumor microenvironment differences between African American and Caucasian American prostate cancer patients and makes suggestion regarding their potential significance in prostate cancer disparities.

Identification of cuproptosis-related lncRNA prognostic signature for osteosarcoma

BACKGROUND

Copper is an indispensably mineral element involved in various metabolic processes and functions in the active sites of many metalloproteins. Copper dysregulation is associated with cancers such as osteosarcoma (OS), the most common primary bone malignancy with invasiveness and metastasis. However, the causality between cuproptosis and OS remains elusive. We aim to identify cuproptosis-related long non-coding RNAs (lncRNAs) for osteosarcomatous prognosis, immune microenvironment response, and immunotherapy.

METHODS

The Person correlation and differential expression analysis were used to identify differentially expressed cuproptosis-related lncRNAs (CRLs). The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were performed to construct the CRL signature. The Kaplan-Meier (K-M) survival analysis, receiver operating characteristic (ROC) curve, internal validation, independent prognostic analysis, and nomograph were used to evaluate the prognostic value. The functional enrichment, tumor microenvironment, immunotherapy and chemotherapy response between the two distinct groups were further explored using a series of algorithms. The expression of signature CRLs was verified by real-time quantitative polymerase chain reaction (RT-qPCR) in OS cell lines.

RESULTS

A novel CRL signature consisting of four CRLs were successfully identified. The K-M survival analysis indicated that the OS patients in the low-risk groups had a better prognosis than that in the high-risk group. Then, the ROC curve and subgroup survival analysis confirmed the prognostic evaluation performance of the signature. Equally, the independent prognostic analysis demonstrated that the CRL signature was an independently predicted factor for OS. Friends analysis determined the hub genes that played a critical role in differentially expressed genes between two distinct risk groups. In addition, the risk score was related to immunity status, immunotherapy response, and chemotherapeutic drug sensitivity. Finally, the expression of these signature CRLs detected by RT-qPCR was consistent with the bioinformatic analysis results.

CONCLUSION

In summary, our study confirmed that the novel CRL signature could effectively evaluate prognosis, tumor immune microenvironment, and immunotherapy response in OS. It may benefit for clinical decision-making and provide new insights for personalized therapeutics.

CD40LG as a Prognostic Molecular Marker Regulates Tumor Microenvironment Through Immune Process in Breast Cancer

Purpose

Breast cancer (BRCA) is the second most common malignancy in the world and the most common in women. Here, we utilized publicly available BRCA dataset to investigate potential prognosis-related genes through integrated bioinformatics analysis.

Materials and Methods

BRCA dataset was obtained from the Cancer Genome Atlas (TCGA) database. The ESTIMATE algorithm was used to calculate the ImmuneScores and StromalScores of the samples and then divided them into high- and low-score groups based on the median score. Common differentially expressed genes (DEGs) were identified through differential expression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. The core prognostic genes were the intersection of hub genes from PPI network and prognostic genes from univariate Cox proportional hazard regression analysis. Finally, the CIBERSORT algorithm was used to calculate proportions of 22 tumor-infiltrating immune cells (TICs) in BRCA samples.

Results

A total of 486 DEGs were identified. These genes were mainly enriched in immune-related pathways. Crossover genes between the hub genes and the prognostic genes were CD2 and CD40LG. CD40LG was further investigated in this study. CD40LG was downregulated in BRCA samples compared with normal samples, and a lower CD40LG expression was associated with advanced tumor stages and a poor prognosis. CD40LG was shown to be involved in immune-related pathways of BRCA by Gene Set Enrichment Analysis. Finally, 14 TICs were found to have a close relationship with CD40LG.

Conclusion

CD40LG was found to be a core prognostic gene related to tumor microenvironment and deeply involved in immune-related pathways in BRCA. Our findings may provide new insights for exploring the molecular mechanisms of BRCA and developing new immunotherapies for the disease.

Immune Infiltration of MMP14 in Pan Cancer and Its Prognostic Effect on Tumors

Background

Matrix metalloproteinase 14 (MMP14) is a member of the MMP family, which interacts with tissue inhibitors of metalloproteinase (TIMPs), and is involved in normal physiological functions such as cell migration, invasion, metastasis, angiogenesis, and proliferation, as well as tumor genesis and progression. However, there has been a lack of relevant reports on the effect of MMP14 across cancers. This study aims to explore the correlation between MMP14 and pan-cancer prognosis, immune infiltration, and the effects of pan-cancer gene mismatch repair (MMR), microsatellite instability (MSI), tumor mutational burden (TMB), DNA methylation, and immune checkpoint genes.

Methods

In this study, we used bioinformatics to analyze data from multiple databases, including The Cancer Genome Atlas (TCGA), ONCOMINE, and Kaplan–Meier plotter. We investigated the relationship between the expression of MMP14 in tumors and tumor prognosis, the relationship between MMP14 expression and tumor cell immune infiltration, and the relationship between MMR gene MMR, MSI, TMB, DNA methylation, and immune checkpoint genes.

Results

MMP14 expression is highly associated with the prognosis of a variety of cancers and tumor immune invasion and has important effects on pan oncologic MMR, MSI, TMB, DNA methylation, and immune checkpoint genes.

Conclusion

MMP14 is highly correlated with tumor prognosis and immune invasion and affects the occurrence and progression of many tumors. All of these results fully indicate that MMP14 may be a biomarker for the prognosis, diagnosis, and treatment of many tumors and provide new ideas and direction for subsequent tumor immune research and treatment strategies.

Identification of Tumor Microenvironment-Related Prognostic lncRNAs in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most common type of lung cancer and is a severe threat to human health. Although many therapies have been applied to LUAD, the long-term survival rate of patients remains unsatisfactory. We aim to find reliable immune microenvironment-related lncRNA biomarkers to improve LUAD prognosis.

Methods

ESTIMATE analysis was performed to evaluate the degree of immune infiltration of each patient in TAGA LUAD cohort. Correlation analysis was used to identify the immune microenvironment-related lncRNAs. Univariate cox regression analysis, LASSO analysis, and Kaplan Meier analysis were used to construct and validate the prognostic model based on microenvironment-related lncRNAs.

Results

We obtained 1,178 immune microenvironment-related lncRNAs after correlation analysis. One hundred and eighty of them are independent prognostic lncRNAs. Sixteen key lncRNAs were selected by LASSO method. This lncRNA-based model successfully predicted patients’ prognosis in validation cohort, and the risk score was related to pathological stage. Besides, we also found that TP53 had the highest frequency mutation in LUAD, and the mutation of TP53 in the high-risk group, which was identified by our survival model, has a poor prognosis. lncRNA-mRNA co-expression network further suggested that these lncRNAs play a vital role in the prognosis of LUAD.

Conclusion

Here, we filtered 16 key lncRNAs, which could predict the survival of LUAD and may be potential biomarkers and therapeutic targets.

A Novel Immune and Stroma Related Prognostic Marker for Invasive Breast Cancer in Tumor Microenvironment: A TCGA Based Study

BACKGROUND

Breast cancer (BC) is the most frequent cancer in women. The tumor microenvironment (TME), consisting of blood vessels, immune cells, fibroblasts, and extracellular matrix, plays a pivotal role in tumorigenesis and progression. Increasing evidence has emphasized the importance of TME, especially the immune components, in patients with BC. Nevertheless, we still lack a deep understanding of the correlation between tumor invasion and TME status.

METHODS

Transcriptome and clinical data were retrieved from The Cancer Genome Atlas (TCGA) database. ESTIMATE algorithm was applied for quantifying stromal and immune scores. Then we screened out the differentially expressed genes (DEGs) through the intersection analysis. Furthermore, the establishment of protein-protein interaction (PPI) network and univariate COX regression analysis were utilized to determine the core genes in DEGs. In addition, we also performed Gene Set Enrichment Analysis (GSEA) and CIBERSORT analysis to distinguish the function of crucial gene expression and the proportion of tumor-infiltrating immune cells (TICs), respectively.

RESULTS

A total of 1178 samples (112 normal samples and 1066 tumor samples) were extracted from TCGA for calculation, and 226 DEGs were obtained from this assessment. Further intersection analysis revealed eight key genes, including ITK, CD3E, CCL19, CD2, SH2D1A, CD5, SLAMF6, SPN, which were proven to correlate with BC status. Moreover, ITK was picked out for further study. The results illustrated that high expression of BC patients had a more prolonged overall survival (OS) time than ITK low expression BC patients (p = 0.009), and ITK expression also presented the statistical significance in age, TNM staging, tumor size classification, and metastasis classification. Additionally, GSEA and CIBERSORT analysis indicated that ITK expression had an association with immune activity in TME.

CONCLUSION

ITK may be a potential indicator for prognosis prediction in patients with BC, and its biological behavior may promote our understanding of the molecular mechanism of tumor progression and targeted therapy.